This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. Background: The Image Based Modeling TRD addresses the goal of using image data to construct geometric models effective for simulation, visualization, and quantitative analysis. While 3D images typically consist of hexahedral grids of measured data, models are geometric objects that represent the underlying biological or anatomical structures. The mechanisms for constructing such models, the geometric and functional representation of these models, and the application and use of the models in a biological context are all highly interrelated. Rationale: This TRD addresses an ongoing demand for software that allows biomedical scientists to quickly build geometric and statistical representations from collections of images. Motivated by the needs of the DBPs and the technical strengths of the investigators and the SCI Institute, the focus of this work is on tools for geometrically adaptive and conforming meshes and statistical models of anatomical and biological shapes. Questions: A closely-related problem in geometric representations is the challenge of building statistical representations of ensembles of image-derived shapes. Our experience, described in this TRD and several of the DBPs and collaborations, is that there is a great demand in the biomedical community for a set of robust tools that allow researchers to represent and quantify shape differences and variability. The future work will focus on technology for the analysis of more complex shapes, adaptations and extensions for application specific needs, and tools for more extensive statistical analyses. Design &Methods: Specific aims fit within three broader objectives. The first is to provide a set of tools for building models that integrates, at one end, the images and various image-based representations of biological systems and, on the other end, simulation, visualization, and analysis. The second objective is to provide an open-source resource to the community, which will allow computer scientists and application scientists to easily construct new results and verify and repeat the experiments of others. The third objective is to provide an infrastructure through which leading-edge tools and resulting research, within and outside the SCI Institute, can be made available to clinicians and the wider biomedical research community.